System and method for enforcing future policies in a compute environment

ABSTRACT

A disclosed system receives a request for resources, generates a credential map for each credential associated with the request, the credential map including a first type of resource mapping and a second type of resource mapping. The system generates a resource availability map, generates a first composite intersecting map that intersects the resource availability map with a first type of resource mapping of all the generated credential maps and generates a second composite intersecting map that intersects the resource availability map and a second type of resource mapping of all the generated credential maps. With the first and second composite intersecting maps, the system can allocate resources within the compute environment for the request based on at least one of the first composite intersecting map and the second composite intersecting map.

RELATED APPLICATIONS

The present application is a continuation of U.S. patent applicationSer. No. 13/362,243, filed Jan. 31, 2012, which is a continuation ofU.S. patent application Ser. No. 10/530,575, filed Mar. 11, 2005, whichis a national phase application of PCT/US05/008299, filed Mar. 11, 2005,the content of which are incorporated herein by reference in theirentirety.

The present application is related to U.S. patent application Ser. No.10/530,583; U.S. patent application Ser. No. 10/530,582; U.S. patentapplication Ser. No. 10/530,581; U.S. patent application Ser. No.10/530,577; U.S. patent application Ser. No. 10/530,576; U.S. patentapplication Ser. No. 10/589,339; U.S. patent application Ser. No.10/530,578; and U.S. patent application Ser. No. 10/530,580, filed onthe same day as the present application. The content of each of thesecases is incorporated herein by reference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to managing policies for access toresources within a compute environment such as a cluster or a grid andmore specifically to a system and method of managing and enforcingfuture policies within the compute environment.

2. Introduction

There are challenges in the complex process of managing the consumptionof resources within a compute environment such as a grid, compute farmor cluster of computers. Grid computing may be defined as coordinatedresource sharing and problem solving in dynamic, multi-institutionalcollaborations. Many computing projects require much more computationalpower and resources than a single computer may provide. Networkedcomputers with peripheral resources such as printers, scanners, I/Odevices, storage disks, scientific devices and instruments, etc. mayneed to be coordinated and utilized to complete a task. The term computeresource generally refers to computer processors, network bandwidth, andany of these peripheral resources as well. A compute farm may comprise aplurality of computers coordinated for such purposes of handlingInternet traffic. The web search website Google® had a compute farm usedto process its network traffic and Internet searches.

Grid/cluster resource management generally describes the process ofidentifying requirements, matching resources to applications, allocatingthose resources, and scheduling and monitoring grid resources over timein order to run grid applications or jobs submitted to the computeenvironment as efficiently as possible. Each project or job will utilizea different set of resources and thus is typically unique. For example,a job may utilize computer processors and disk space, while another jobmay require a large amount of network bandwidth and a particularoperating system. In addition to the challenge of allocating resourcesfor a particular job or a request for resources, administrators alsohave difficulty obtaining a clear understanding of the resourcesavailable, the current status of the compute environment and availableresources, and real-time competing needs of various users. One aspect ofthis process is the ability to reserve resources for a job. A clustermanager will seek to reserve a set of resources to enable the cluster toprocess a job at a promised quality of service.

The reservation of resources will also be in compliance with user orgroup credentials. For example, a user may be limited to the use of 10processors per job or 10 processors at any given time. Other credentialsmay be limits related to an earliest start time, a certain quality ofservice, and so forth. A group such as a science or marketing departmentmay be limited as to the number of processors it may use at any giventime. As reservations of resources are made, the system not only mustidentify available resources but must make reservations consistent withthe limits on each particular user or group of users.

General background information on clusters and grids may be found inseveral publications. See, e.g., Grid Resource Management, State of theArt and Future Trends, Jarek Nabrzyski, Jennifer M. Schopf, and JanWeglarz, Kluwer Academic Publishers, 2004; and Beowulf Cluster Computingwith Linux, edited by William Gropp, Ewing Lusk, and Thomas Sterling,Massachusetts Institute of Technology, 2003.

It is generally understood herein that the terms grid and cluster areinterchangeable, although they have different connotations. For example,when a grid is referred to as receiving a request for resources and therequest is processed in a particular way, the same method may also applyto other compute environments such as a cluster or a compute farm. Acluster is generally defined as a collection of compute nodes organizedfor accomplishing a task or a set of tasks. In general, a grid willcomprise a plurality of clusters as will be shown in FIG. 1A. Severalgeneral challenges exist when attempting to maximize resources in agrid. First, there are typically multiple layers of grid and clusterschedulers. A grid 100 generally comprises a group of clusters or agroup of networked computers. The definition of a grid is very flexibleand may mean a number of different configurations of computers. Theintroduction here is meant to be general given the variety ofconfigurations that are possible. A grid scheduler 102 communicates witha plurality of cluster schedulers 104A, 104B and 104C. Each of thesecluster schedulers communicates with a respective resource manager 106A,106B or 106C. Each resource manager communicates with a respectiveseries of compute resources shown as nodes 108A, 108B, 108C in cluster110, nodes 108D, 108E, 108F in cluster 112 and nodes 108G, 108H, 108I incluster 114.

Local schedulers (which may refer to either the cluster schedulers 104or the resource managers 106) are closer to the specific resources 108and may not allow grid schedulers 102 direct access to the resources.The grid level scheduler 102 typically does not own or control theactual resources. Therefore, jobs are submitted from the high levelgrid-scheduler 102 to a local set of resources with no more permissionsthat then user would have. This reduces efficiencies and can render thereservation process more difficult.

The heterogeneous nature of the shared compute resources also causes areduction in efficiency. Without dedicated access to a resource, thegrid level scheduler 102 is challenged with the high degree of varianceand unpredictability in the capacity of the resources available for use.Most resources are shared among users and projects and each projectvaries from the other. The performance goals for projects differ. Gridresources are used to improve performance of an application but theresource owners and users have different performance goals: fromoptimizing the performance for a single application to getting the bestsystem throughput or minimizing response time. Local policies may alsoplay a role in performance.

Within a given cluster, there is only a concept of resource managementin space. An administrator can partition a cluster and identify a set ofresources to be dedicated to a particular purpose and another set ofresources can be dedicated to another purpose. In this regard, theresources are reserved in advance to process the job. There is currentlyno ability to identify a set of resources over a time frame for apurpose. By being constrained in space, the nodes 108A, 108B, 108C, ifthey need maintenance or for administrators to perform work orprovisioning on the nodes, have to be taken out of the system,fragmented permanently or partitioned permanently for special purposesor policies. If the administrator wants to dedicate them to particularusers, organizations or groups, the prior art method of resourcemanagement in space causes too much management overhead requiring aconstant adjustment the configuration of the cluster environment andalso losses in efficiency with the fragmentation associated with meetingparticular policies.

To manage the jobs submissions or requests for resources within acluster, a cluster scheduler will employ reservations to insure thatjobs will have the resources necessary for processing. FIG. 1Billustrates a cluster/node diagram for a cluster 124 with nodes 120.Time is along the X axis. An access control list 114 (ACL) to thecluster is static, meaning that the ACL is based on the credentials ofthe person, group, account, class or quality of service making therequest or job submission to the cluster. The ACL 114 determines whatjobs get assigned to the cluster 110 via a reservation 112 shown asspanning into two nodes of the cluster. Either the job can be allocatedto the cluster or it can't and the decision is determined based on whosubmits the job at submission time. The deficiency with this approach isthat there are situations in which organizations would like to makeresources available but only in such a way as to balance or meet certainperformance goals. Particularly, groups may want to establish a constantexpansion factor and make that available to all users or they may wantto make a certain subset of users that are key people in an organizationand want to give them special services but only when their response timedrops below a certain threshold. Given the prior art model, companiesare unable to have the flexibility over their cluster resources.

As resources are reserved in the future for jobs submitted by a personor a group, there are challenges in the process where not all availableresources may be known for a given set of constraints such that thereservation may be made at an optimal time for the submitter.Constraints on the use of resources may relate to such parameters asuser or group privileges, resource use restraints, quality of serviceconstraints and so forth. What is needed in the art is a system andmethod that enables an improved reservation of resources given knownconstraints.

SUMMARY OF THE INVENTION

Additional features and advantages of the invention will be set forth inthe description which follows, and in part will be obvious from thedescription, or may be learned by practice of the invention. Thefeatures and advantages of the invention may be realized and obtained bymeans of the instruments and combinations particularly pointed out inthe appended claims. These and other features of the present inventionwill become more fully apparent from the following description andappended claims, or may be learned by the practice of the invention asset forth herein.

The invention relates to a system, method and computer-readable medium,as well as grids and clusters managed according to the method describedherein. An example embodiment relates to a method of processing arequest for resources within a compute environment. The method ispracticed by a system that contains modules configured or programmed tocarry out the steps of the invention. The system receives a request forresources, generates a credential map for each credential associatedwith the request, the credential map comprising a first type of resourcemapping and a second type of resource mapping. The system generates aresource availability map, generates a first composite intersecting mapthat intersects the resource availability map with a first type ofresource mapping of all the generated credential maps and generates asecond composite intersecting map that intersects the resourceavailability map and a second type of resource mapping of all thegenerated credential maps. With the first and second compositeintersecting maps, the system can allocate resources within the computeenvironment for the request based on at least one of the first compositeintersecting map and the second composite intersecting map. Theallocations or reservation for the request can then be made in anoptimal way for parameters such as the earliest time possible based onavailable resources and also that maintains the constraints on therequestor.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to describe the manner in which the above-recited and otheradvantages and features of the invention can be obtained, a moreparticular description of the invention briefly described above will berendered by reference to specific embodiments thereof which areillustrated in the appended drawings. Understanding that these drawingsdepict only typical embodiments of the invention and are not thereforeto be considered to be limiting of its scope, the invention will bedescribed and explained with additional specificity and detail throughthe use of the accompanying drawings in which:

FIG. 1A illustrates generally a grid scheduler, cluster scheduler, andresource managers interacting with compute nodes within plurality ofclusters;

FIG. 1B illustrates an access control list which provides access toresources within a compute environment;

FIG. 2A illustrates a plurality of reservations made for computeresources;

FIG. 2B illustrates a plurality of reservations and jobs submittedwithin those reservations;

FIG. 3 illustrates a dynamic access control list;

FIG. 4 illustrates a reservation creation window;

FIG. 5 illustrates a dynamic reservation migration process;

FIGS. 6A-C illustrate examples of various concepts associated with anembodiment; and

FIG. 7 illustrates a method embodiment of the invention.

DETAILED DESCRIPTION OF THE INVENTION

Various embodiments of the invention are discussed in detail below.While specific implementations are discussed, it should be understoodthat this is done for illustration purposes only. A person skilled inthe relevant art will recognize that other components and configurationsmay be used without parting from the spirit and scope of the invention.The claims in this application primarily focus on the disclosureassociated with FIGS. 6 and 7.

The present invention relates to reservations of resources within thecontext of a compute environment. One example of a compute environmentis a cluster. The cluster may be, for example, a group of computingdevices operated by a hosting facility, a hosting center, a virtualhosting center, a data center, grid and/or utility-based computingenvironments. Every reservation consists of three major components: aset of resources, a timeframe, and an access control list (ACL).Additionally, a reservation may also have a number of optionalattributes controlling its behavior and interaction with other aspectsof scheduling. A reservation's ACL specifies which jobs can use thereservation. Only jobs which meet one or more of a reservation's accesscriteria are allowed to use the reserved resources during thereservation timeframe. The reservation access criteria comprises, in oneexample, at least following: users, groups, accounts, classes, qualityof service (QOS) and job duration. A job may be any venue or end ofconsumption of resource for any broad purpose, whether it be for a batchsystem, direct volume access or other service provisioning.

A workload manager, or scheduler, will govern access to the computeenvironment by receiving requests for reservations of resources andcreating reservations for processing jobs. A workload manager functionsby manipulating five primary, elementary objects. These are jobs, nodes,reservations, QOS structures, and policies. In addition to these,multiple minor elementary objects and composite objects are alsoutilized. These objects are also defined in a scheduling dictionary.

A workload manager may operate on a single computing device or multiplecomputing devices to manage the workload of a compute environment. The“system” embodiment of the invention may comprise a computing devicethat includes the necessary hardware and software components to enable aworkload manager or a software module performing the steps of theinvention. Such a computing device may include such known hardwareelements as one or more central processors, random access memory (RAM),read-only memory (ROM), storage devices such as hard disks,communication means such as a modem or a card to enable networking withother computing devices, a bus that provides data transmission betweenvarious hardware components, a keyboard, a display, an operating systemand so forth. There is no restriction that the particular systemembodiment of the invention have any specific hardware components andany known or future developed hardware configurations are contemplatedas within the scope of the invention when the computing device operatesas is claimed.

Job information is provided to the workload manager scheduler from aresource manager such as Loadleveler, the Portable Batch System (PBS),Wiki or Platform's LSF products. Those of skill in the art will befamiliar with each of these software products and their variations. Jobattributes include ownership of the job, job state, amount and type ofresources required by the job, required criteria (I need this jobfinished in 1 hour), preferred criteria (I would like this job tocomplete in ½ hour) and a wallclock limit, indicating how long theresources are required. A job consists of one or more requirements eachof which requests a number of resources of a given type. For example, ajob may consist of two requirements, the first asking for ‘1 IBM nodewith at least 512 MB of RAM’ and the second asking for ‘24 IBM nodeswith at least 128 MB of RAM’. Each requirement consists of one or moretasks where a task is defined as the minimal independent unit ofresources. A task is a collection of elementary resources which must beallocated together within a single node. For example, a task may consistof one processor, 512 MB or memory, and 2 GB of local disk. A task mayalso be just a single processor. In symmetric multiprocessor (SMP)environments, however, users may wish to tie one or more processorstogether with a certain amount of memory and/or other resources. A keyaspect of a task is that the resources associated with the task must beallocated as an atomic unit, without spanning node boundaries. A taskrequesting 2 processors cannot be satisfied by allocating 2uni-processor nodes, nor can a task requesting 1 processor and 1 GB ofmemory be satisfied by allocating 1 processor on one node and memory onanother.

A job requirement (or req) consists of a request for a single type ofresources. Each requirement consists of the following components: (1) atask definition is a specification of the elementary resources whichcompose an individual task; (2) resource constraints provide aspecification of conditions which must be met in order for resourcematching to occur. Only resources from nodes which meet all resourceconstraints may be allocated to the job requirement; (3) a task countrelates to the number of task instances required by the requirement; (4)a task List is a list of nodes on which the task instances have beenlocated; and (5) requirement statistics are statistics tracking resourceutilization.

As far as the workload manager is concerned, a node is a collection ofresources with a particular set of associated attributes. In most cases,it fits nicely with the canonical world view of a node such as a PCcluster node or an SP node. In these cases, a node is defined as one ormore CPU's, memory, and possibly other compute resources such as localdisk, swap, network adapters, software licenses, etc. Additionally, thisnode will described by various attributes such as an architecture typeor operating system. Nodes range in size from small uni-processor PC'sto large SMP systems where a single node may consist of hundreds ofCPU's and massive amounts of memory.

Information about nodes is provided to the scheduler chiefly by theresource manager. Attributes include node state, configured andavailable resources (i.e., processors, memory, swap, etc.), run classessupported, etc.

Policies are generally specified via a configuration file and serve tocontrol how and when jobs start. Policies include, but are not limitedto, job prioritization, fairness policies, fairshare configurationpolicies, and scheduling policies. Jobs, nodes, and reservations alldeal with the abstract concept of a resource. A resource in the workloadmanager world is one of the following: (1) processors which arespecified with a simple count value; (2) memory such as real memory or‘RAM’ is specified in megabytes (MB); (3) swap which is virtual memoryor ‘swap’ is specified in megabytes (MB); and (4) disk space such as alocal disk is specified in megabytes (MB) or gigabytes (GB). In additionto these elementary resource types, there are two higher level resourceconcepts used within workload manager. These are the task and theprocessor equivalent (PE).

In a workload manager, jobs or reservations that request resources makesuch a request in terms of tasks typically using a task count and a taskdefinition. By default, a task maps directly to a single processorwithin a job and maps to a full node within reservations. In all cases,this default definition can be overridden by specifying a new taskdefinition. Within both jobs and reservations, depending on taskdefinition, it is possible to have multiple tasks from the same jobmapped to the same node. For example, a job requesting 4 tasks using thedefault task definition of 1 processor per task, can be satisfied by twodual processor nodes.

The concept of the PE arose out of the need to translate multi-resourceconsumption requests into a scalar value. It is not an elementaryresource, but rather, a derived resource metric. It is a measure of theactual impact of a set of requested resources by a job on the totalresources available system wide. It is calculated as:PE=MAX(ProcsRequestedByJob/TotalConfiguredProcs,MemoryRequestedByJob/TotalConfiguredMemory,DiskRequestedByJob/TotalConfiguredDisk,SwapRequestedByJob/TotalConfiguredSwap)*TotalConfiguredProcs

For example, say a job requested 20% of the total processors and 50% ofthe total memory of a 128 processor MPP system. Only two such jobs couldbe supported by this system. The job is essentially using 50% of allavailable resources since the system can only be scheduled to its mostconstrained resource, in this case memory. The processor equivalents forthis job should be 50% of the PE=64.

A further example will be instructive. Assume a homogeneous 100 nodesystem with 4 processors and 1 GB of memory per node. A job is submittedrequesting 2 processors and 768 MB of memory. The PE for this job wouldbe calculated as:PE=MAX(2/(100*4),768/(100*1024))*(100*4)=3.

This result makes sense since the job would be consuming ¾ of the memoryon a 4 processor node. The calculation works equally well on homogeneousor heterogeneous systems, uni-processor or large way SMP systems.

A class (or queue) is a logical container object which can be used toimplicitly or explicitly apply policies to jobs. In most cases, a classis defined and configured within the resource manager and associatedwith one or more of the attributes or constraints shown in Table 1below.

TABLE 1 Attributes of a Class Attribute Description Default Job A queuemay be associated with a default job duration, Attributes default size,or default resource requirements Host A queue may constrain jobexecution to a particular Constraints set of hosts Job Constraints Aqueue may constrain the attributes of jobs which may submitted includingsetting limits such as max wallclock time, minimum number of processors,etc. Access List A queue may constrain who may submit jobs into it basedon user lists, group lists, etc. Special Access A queue may associatespecial privileges with jobs including adjusted job priority.

As stated previously, most resource managers allow full classconfiguration within the resource manager. Where additional classconfiguration is required, the CLASSCFG parameter may be used. Theworkload manager tracks class usage as a consumable resource allowingsites to limit the number of jobs using a particular class. This is doneby monitoring class initiators which may be considered to be a ticket torun in a particular class. Any compute node may simultaneously supportseveral types of classes and any number of initiators of each type. Bydefault, nodes will have a one-to-one mapping between class initiatorsand configured processors. For every job task run on the node, one classinitiator of the appropriate type is consumed. For example, a threeprocessor job submitted to the class batch will consume three batchclass initiators on the nodes where it is run.

Using queues as consumable resources allows sites to specify variouspolicies by adjusting the class initiator to node mapping. For example,a site running serial jobs may want to allow a particular 8 processornode to run any combination of batch and special jobs subject to thefollowing constraints:

-   -   only 8 jobs of any type allowed simultaneously    -   no more than 4 special jobs allowed simultaneously

To enable this policy, the site may set the node's MAXJOB policy to 8and configure the node with 4 special class initiators and 8 batch classinitiators. Note that in virtually all cases jobs have a one-to-onecorrespondence between processors requested and class initiatorsrequired. However, this is not a requirement and, with specialconfiguration sites may choose to associate job tasks with arbitrarycombinations of class initiator requirements.

In displaying class initiator status, workload manager signifies thetype and number of class initiators available using the format[<CLASSNAME>:<CLASSCOUNT>]. This is most commonly seen in the output ofnode status commands indicating the number of configured and availableclass initiators, or in job status commands when displaying classinitiator requirements.

Nodes can also be configured to support various arbitrary resources.Information about such resources can be specified using the NODECFGparameter. For example, a node may be configured to have “256 MB RAM, 4processors, 1 GB Swap, and 2 tape drives”.

We next turn to the concept of reservations. There are several types ofreservations which sites typically deal with. The first, administrativereservations, are typically one-time reservations created for specialpurposes and projects. These reservations are created using a commandthat sets a reservation. These reservations provide an integratedmechanism to allow graceful management of unexpected system maintenance,temporary projects, and time critical demonstrations. This commandallows an administrator to select a particular set of resources or justspecify the quantity of resources needed. For example, an administratorcould use a regular expression to request a reservation be created onthe nodes ‘blue0[1-9]’ or could simply request that the reservationlocate the needed resources by specifying a quantity based request suchas ‘TASKS==20’.

Another type of reservation is called a standing reservation. This isshown in FIG. 2A. A standing reservation is useful for recurring needsfor a particular type of resource distribution. For example, a sitecould use a standing reservation to reserve a subset of its computeresources for quick turnaround jobs during business hours on Monday thruFriday. Standing reservations are created and configured by specifyingparameters in a configuration file.

As shown in FIG. 2A, the compute environment 202 includes standingreservations shown as 204A, 204B and 204C. These reservations showresources allocated and reserved on a periodic basis. These are, forexample, consuming reservations meaning that cluster resources will beconsumed by the reservation. These reservations are specific to a useror a group of users and allow the reserved resources to be alsocustomized specific to the workload submitted by these users or groups.For example, one aspect of the invention is that a user may have accessto reservation 204A and not only submit jobs to the reserved resourcesbut request, perhaps for optimization or to meet preferred criteria asopposed to required criteria, that the resources within the reservationbe modified by virtual partitioning or some other means to accommodatethe particular submitted job. In this regard, this embodiment of theinvention enables the user to submit and perhaps request modification oroptimization within the reserved resources for that particular job.There may be an extra charge or debit of an account of credits for themodification of the reserved resources. The modification of resourceswithin the reservation according to the particular job may also beperformed based on a number of factors discussed herein, such ascriteria, class, quality of service, policies etc.

Standing reservations build upon the capabilities of advancereservations to enable a site to enforce advanced usage policies in anefficient manner. Standing reservations provide a superset of thecapabilities typically found in a batch queuing system's class or queuearchitecture. For example, queues can be used to allow only particulartypes of jobs access to certain compute resources. Also, some batchsystems allow these queues to be configured so that they only allow thisaccess during certain times of the day or week. Standing reservationsallow these same capabilities but with greater flexibility andefficiency than is typically found in a normal queue management system.

Standing Reservations provide a mechanism by which a site can dedicate aparticular block of resources for a special use on a regular daily orweekly basis. For example, node X could be dedicated to running jobsonly from users in the accounting group every Friday from 4 to 10 PM. Astanding reservation is a powerful means of controlling access toresources and controlling turnaround of jobs.

Another embodiment of reservation is something called a reservationmask, which allows a site to create “sandboxes” in which otherguarantees can be made. The most common aspects of this reservation arefor grid environments and personal reservation environments. In a gridenvironment, a remote entity will be requesting resources and will wantto use these resources on an autonomous cluster for the autonomouscluster to participate. In many cases it will want to constrain when andwhere the entities can reserve or utilize resources. One way of doingthat is via the reservation mask.

FIG. 2B illustrates the reservation mask shown as creating sandboxes206A, 206B, 206C in compute environment 210 and allows the autonomouscluster to state that only a specific subset of resources can be used bythese remote requesters during a specific subset of times. When arequester asks for resources, the scheduler will only report and returnresources available within this reservation, after which point theremote entity desires it, it can actually make a consumption reservationand that reservation is guaranteed to be within the reservation maskspace. The consumption reservations 212A, 212B, 212C, 212D are shownwithin the reservation masks.

Another concept related to reservations is the personal reservationand/or the personal reservation mask. In compute environment 210, thereservation masks operate differently from consuming reservations inthat they are enabled to allow personal reservations to be createdwithin the space that is reserved. ACL's are independent inside of asandbox reservation or a reservation mask in that you can also excludeother requesters out of those spaces so they're dedicated for theseparticular users.

One benefit of the personal reservation approach includes preventinglocal job starvation, and providing a high level of control to thecluster manager in that he or she can determine exactly when, where, howmuch and who can use these resources even though he doesn't necessarilyknow who the requesters are or the combination or quantity of resourcesthey will request. The administrator can determine when, how and whererequestors will participate in these clusters or grids. A valuable useis in the space of personal reservations which typically involves alocal user given the authority to reserve a block of resources for arigid time frame. Again, with a personal reservation mask, the requestsare limited to only allow resource reservation within the mask timeframe and mask resource set, providing again the administrator theability to constrain exactly when and exactly where and exactly how muchof resources individual users can reserve for a rigid time frame. Theindividual user is not known ahead of time but it is known to thesystem, it is a standard local cluster user.

The reservation masks 206A, 206B and 206C define periodic, personalreservation masks where other reservations in the compute environment210 may be created, i.e., outside the defined boxes. These areprovisioning or policy-based reservations in contrast to consumingreservations. In this regard, the resources in this type of reservationare not specifically allocated but the time and space defined by thereservation mask cannot be reserved for other jobs. Reservation masksenable the system to be able to control the fact that resources areavailable for specific purposes, during specific time frames. The timeframes may be either single time frames or repeating time frames todedicate the resources to meet project needs, policies, guarantees ofservice, administrative needs, demonstration needs, etc. This type ofreservation insures that reservations are managed and scheduled in timeas well as space. Boxes 208A, 208B, 208C and 208D represent non-personalreservation masks. They have the freedom to be placed anywhere incluster including overlapping some or all of the reservation masks 206A,206B, 206C. Overlapping is allowed when the personal reservation maskwas setup with a global ACL. To prevent the possibility of an overlap ofa reservation mask by a non-personal reservation, the administrator canset an ACL to constrain it is so that only personal consumptionreservations are inside. These personal consumption reservations areshown as boxes 212B, 212A, 212C, 212D which are constrained to be withinthe personal reservation masks 206A, 206B, 206C. The 208A, 208B, 208Cand 208D reservations, if allowed, can go anywhere within the cluster210 including overlapping the other personal reservation masks. Theresult is the creation of a “sandbox” where only personal reservationscan go without in any way constraining the behavior of the scheduler toschedule other requests.

All reservations possess a start and an end time which define thereservation's active time. During this active time, the resources withinthe reservation may only be used as specified by the reservation ACL.This active time may be specified as either a start/end pair or astart/duration pair. Reservations exist and are visible from the timethey are created until the active time ends at which point they areautomatically removed.

For a reservation to be useful, it must be able to limit who or what canaccess the resources it has reserved. This is handled by way of anaccess control list, or ACL. With reservations, ACL's can be based oncredentials, resources requested, or performance metrics. In particular,with a standing reservation, the attributes userlist, grouplist,accountlist, classlist, qoslist, jobattrlist, proclimit, timelimit andothers may be specified.

FIG. 3 illustrates an aspect of the present invention that allows theACL 306 for the reservation 304 to have a dynamic aspect instead ofsimply being based on who the requester is. The ACL decision-makingprocess is based at least in part on the current level of service orresponse time that is being delivered to the requester. To illustratethe operation of the ACL 306, assume that a user 308 submits a job 314to a queue 310 and that the ACL 306 reports that the only job that canaccess these resources 302 are those that have a queue time thatcurrently exceeds two hours. The resources 302 are shown with resourcesN on the y axis and time on the x axis. If the job 314 has sat in thequeue 310 for two hours it will then access the additional resources toprevent the queue time for the user 308 from increasing significantlybeyond this time frame. The decision to allocate these additionalresources can be keyed off of utilization of an expansion factor andother performance metrics of the job. For example, the reservation 304may be expanded or contracted or migrated to cover a new set ofresources.

Whether or not an ACL 306 is satisfied is typically and preferablydetermined the scheduler 104A. However, there is no restriction in theprinciple of the invention regarding where or on what node in thenetwork the process of making these allocation of resource decisionsoccurs. The scheduler 104A is able to monitor all aspects of the requestby looking at the current job 314 inside the queue 310 and how long ithas sat there and what the response time target is and the scheduleritself determines whether all requirements of the ACL 306 are satisfied.If requirements are satisfied, it releases the resources that areavailable to the job 314. A job 314 that is located in the queue and thescheduler communicating with the scheduler 104A. If resources areallocated, the job 314 is taken from the queue 310 and inserted into thereservation 314 in the cluster 302.

An example benefit of this model is that it makes it significantlyeasier for a site to balance or provide guaranteed levels of service orconstant levels of service for key players or the general populace. Bysetting aside certain resources and only making them available to thejobs which threaten to violate their quality of service targets, thesystem increases the probability of satisfying targets.

When specifying which resources to reserve, the administrator has anumber of options. These options allow control over how many resourcesare reserved and where they are reserved at. The following reservationattributes allow the administrator to define resources.

An important aspect of reservations is the idea of a task. The scheduleruses the task concept extensively for its job and reservationmanagement. A task is simply an atomic collection of resources, such asprocessors, memory, or local disk, which must be found on the same node.For example, if a task requires 4 processors and 2 GB of memory, thescheduler must find all processors AND memory on the same node; itcannot allocate 3 processors and 1 GB on one node and 1 processor and 1GB of memory on another node to satisfy this task. Tasks constrain howthe scheduler must collect resources for use in a standing reservation,however, they do not constrain the way in which the scheduler makesthese cumulative resources available to jobs. A job can use theresources covered by an accessible reservation in whatever way it needs.If reservation X allocated 6 tasks with 2 processors and 512 MB ofmemory each, it could support job Y which requires 10 tasks of 1processor and 128 MB of memory or job Z which requires 2 tasks of 4processors and 1 GB of memory each. The task constraints used to acquirea reservation's resources are completely transparent to a job requestinguse of these resources. Using the task description, the taskcountattribute defines how many tasks must be allocated to satisfy thereservation request. To create a reservation, a taskcount and/or ahostlist may be specified.

A hostlist constrains the set of resource which are available to areservation. If no taskcount is specified, the reservation will attemptto reserve one task on each of the listed resources. If a taskcount isspecified which requests fewer resources than listed in the hostlist,the scheduler will reserve only the number of tasks from the hostlistspecified by the taskcount attribute. If a taskcount is specified whichrequests more resources than listed in the hostlist, the scheduler willreserve the hostlist nodes first and then seek additional resourcesoutside of this list.

Reservation flags allow specification of special reservation attributesor behaviors. Supported flags are listed in table 2 below.

TABLE 2 Flag Name Description BESTEFFORT N/A BYNAME reservation willonly allow access to jobs which meet reservation ACL's and explicitlyrequest the resources of this reservation using the job ADVRES flagIGNRSV request will ignore existing resource reservations allowing thereservation to be forced onto available resources even if this conflictswith other reservations. OWNERPREEMPT job's by the reservation owner areallowed to preempt non-owner jobs using reservation resources PREEMPTEEPreempts a job or other object SINGLEUSE reservation is automaticallyremoved after completion of the first job to use the reserved resourcesSPACEFLEX reservation is allowed to adjust resources allocated over timein an attempt to optimize resource utilization TIMEFLEX reservation isallowed to adjust the reserved timeframe in an attempt to optimizeresource utilization

Reservations must explicitly request the ability to float foroptimization purposes by using a flag such as the SPACEFLEX flag. Thereservations may be established and then identified as self-optimizingin either space or time. If the reservation is flagged as such, thenafter the reservation is created, conditions within the computeenvironment may be monitored to provide feedback on where optimizationmay occur. If so justified, a reservation may migrate to a new time ormigrate to a new set of resources that are more optimal than theoriginal reservation.

FIG. 4 illustrates a reservation creation window 400 that includes theuse of the flags in Table 2. A user Scott input reservation informationin a variety of fields 402 for name, partition, node features andfloating reservation. Each of these input fields includes a drop-downmenu to enable the selection of options easy. An access control listinput field 404 allows the user to input an account, class/queue, user,group and QoS information. Resources may be assigned and searched andtasks created 406 and reservation flags set 408, such as best effort,single use, preemptee, time flex, by name, owner preempt, space flex,exclusive and force. These flags set parameters that may cause thereservation to be optimized such as in time or space where it migratesto a new time or over new resources based on monitored events or otherfeedback.

A reservation time-frame 410 may also be input such as one, daily,weekly, with start and end times for the reservation. Menu drop downcalendars and clocks are available for easily enabling the user to viewand graphically input and select the various timeframe parameters. Eventtriggers may also be input wherein the user can create one or moretriggers associated with the reservation. As generally shown in FIG. 4,the use of a graphical interface simplifies the reservation-creationprocess for the administrator or user.

FIG. 5 illustrates a particular instance where the user has identifiedthe time-flex and space-flex flags within the reservation. A window 500identifies three reservations 502 for 96 nodes, 504 for 128 nodes and506 for 256 nodes. The height of each of these reservations generallyrelates to resources reserved, such as a number of processors reservedor processors and disk space. The X-axis represents time. Reservation508 represents a reservation in the future that will in a position toreceive submitted jobs. Assume that reservation 506 which was scheduledto end at time T2 has finished early at time T1. Also assume thatreservation 508 is flagged for time flex and space flex. In this case,based on the monitored event that reservation 506 has ended early, thesystem would cause reservation 508 to migrate in time (and space in thisexample) to position 510. This represents a movement of the reservationto a new time and a new set of resources. If reservation 504 ends early,and reservation 508 migrates to position 520, that would represent amigration in time (to an earlier time) but not in space. This would beenabled by the time-flex flag being set wherein the migration would seekto create a new reservation at the earliest time possible and/oraccording to available resources. The new time may be based on criteriato minimize the time for the reservation or to maximize usage of theoverall resources or better performance of the compute environment.

Next, assume that reservation 508 is for 128 processors and reservation506 is for 256 processors and reservation 508 is flagged for space flex.If reservation 506 ends are time T1 instead of time T2, then reservation508 may migrate to position 512 to a reservation of 256 processors. Thetime frame of the starting and ending time may be the same but thereservation has migrated in space and thus been optimized.

In another aspect of reservation migration, assume that reservation 508is set but that a node or a group of nodes that are part of thereservation go down or are projected to fail as represented by 518. Inthis regard, reservation 508 may be enabled to migrate as shown by 516and 508 to cover new resources but to accommodate for the nodes that areno longer available.

Standing reservations allow resources to be dedicated for particularuses. This dedication can be configured to be permanent or periodic,recurring at a regular time of day and/or time of week. There isextensive applicability of standing reservations for everything fromdaily dedicated job runs to improved use of resources on weekends. Allstanding reservation attributes are specified via a parameter usingavailable attributes

In addition to standing and administrative reservations, a workloadmanager according to the invention can also create priorityreservations. These reservations are used to allow the benefits ofout-of-order execution (such as is available with a backfill feature)without the side effect of job starvation. Starvation can occur in anysystem where the potential exists for a job to be overlooked by thescheduler for an indefinite period. In the case of backfill, small jobsmay continue to be run on available resources as they become availablewhile a large job sits in the queue never able to find enough nodesavailable simultaneously to run on. To avoid such situations, priorityreservations are created for high priority jobs which cannot runimmediately. When making these reservations, the scheduler determinesthe earliest time the job could start, and then reserves these resourcesfor use by this job at that future time. By default, only the highestpriority job will receive a priority reservation. However, this behavioris configurable via a reservation depth policy. The workload manager'sdefault behavior of only reserving the highest priority job allowsbackfill to be used in a form known as liberal backfill. This liberalbackfill tends to maximize system utilization and minimize overallaverage job turnaround time. However, it does lead to the potential ofsome lower priority jobs being indirectly delayed and may lead togreater variance in job turnaround time. A reservation depth parametercan be set to a very large value, essentially enabling what is calledconservative backfill where every job which cannot run is given areservation. Most sites prefer the liberal backfill approach associatedwith the default reservation depth 1 or select a slightly higher value.It is important to note that to prevent starvation in conjunction withreservations, monotonically increasing priority factors such asqueuetime or job x-factor should be enabled.

Another important consequence of backfill and reservation depth is itsaffect on job priority. In the workload manager, all jobs are preferablyprioritized. Backfill allows jobs to be run out of order and thus, tosome extent, job priority to be ignored. This effect, known as ‘prioritydilution’ can cause many site policies implemented via workload managerprioritization policies to be ineffective. Setting the reservation depthparameter to a higher value will give job priority ‘more teeth’ at thecost of slightly lower system utilization. This lower utilizationresults from the constraints of these additional reservations,decreasing the scheduler's freedom and its ability to find additionaloptimizing schedules. Anecdotal evidence indicates that theseutilization losses are fairly minor, rarely exceeding 8%.

In addition to the reservation depth parameter, sites also have theability to control how reservations are maintained. The workloadmanager's dynamic job prioritization allows sites to prioritize jobs sothat their priority order can change over time. It is possible that onejob can be at the top of the priority queue for a time, and then getbypassed by another job submitted later. A reservation policy parameterallows a site to determine what how existing reservations should behandled when new reservations are made. The value “highest” will causethat all jobs which have ever received a priority reservation willmaintain that reservation until they run even if other jobs later bypassthem in priority value. The value of the parameter “current highest”will cause that only the current top <RESERVATIONDEPTH> priority jobswill receive reservations. If a job had a reservation but has beenbypassed in priority by another job so that it no longer qualifies asbeing among the top <RESERVATIONDEPTH> jobs, it will lose itsreservation. Finally, the value “never” indicates that no priorityreservations will be made.

QOS-based reservation depths can be enabled via the reservation QOS listparameter. This parameter allows varying reservation depths to beassociated with different sets of job QoS's. For example, the followingconfiguration will create two reservation depth groupings:

---- RESERVATIONDEPTH[0] 8 RESERVATIONQOSLIST[0] highprio interactivedebug RESERVATIONDEPTH[1] 2 RESERVATIONQOSLIST[1] batch ----

This example will cause that the top 8 jobs belonging to the aggregategroup of highprio, interactive, and debug QoS jobs will receive priorityreservations. Additionally, the top 2 batch QoS jobs will also receivepriority reservations. Use of this feature allows sites to maintain highthroughput for important jobs by guaranteeing a significant proportionof these jobs are making progress toward starting through use of thepriority reservation. The following are example default values for someof these parameters: RESERVATIONDEPTH[DEFAULT]=1;

-   -   RESERVATIONQOSLIST[DEFAULT]=ALL.

This allows one job with the highest priority to get a reservation.These values can be overwritten by modifying the default policy.

A final reservation policy is in place to handle a number of real-worldissues. Occasionally when a reservation becomes active and a jobattempts to start, various resource manager race conditions or corruptstate situations will prevent the job from starting. By default, theworkload manager assumes the resource manager is corrupt, releases thereservation, and attempts to re-create the reservation after a shorttimeout. However, in the interval between the reservation release andthe re-creation timeout, other priority reservations may allocate thenewly available resources, reserving them before the originalreservation gets an opportunity to reallocate them. Thus, when theoriginal job reservation is re-established, its original resource may beunavailable and the resulting new reservation may be delayed severalhours from the earlier start time. The parameter reservation retry timeallows a site that is experiencing frequent resource manager raceconditions and/or corruption situations to tell the workload manager tohold on to the reserved resource for a period of time in an attempt toallow the resource manager to correct its state.

Next we discuss the use of partitions. Partitions are a logicalconstruct which divide available resources and any single resource(i.e., compute node) may only belong to a single partition. Often,natural hardware or resource manager bounds delimit partitions such asin the case of disjoint networks and diverse processor configurationswithin a cluster. For example, a cluster may consist of 256 nodescontaining four 64 port switches. This cluster may receive excellentinterprocess communication speeds for parallel job tasks located withinthe same switch but sub-stellar performance for tasks which spanswitches. To handle this, the site may choose to create four partitions,allowing jobs to run within any of the four partitions but not spanthem.

While partitions do have value, it is important to note that within theworkload manager, the standing reservation facility providessignificantly improved flexibility and should be used in the vastmajority of politically motivated cases where partitions may be requiredunder other resource management systems. Standing reservations providetime flexibility, improved access control features, and more extendedresource specification options. Also, another workload manager facilitycalled node sets allows intelligent aggregation of resources to improveper job node allocation decisions. In cases where system partitioning isconsidered for such reasons, node sets may be able to provide a bettersolution.

An important aspect of partitions over standing reservations and nodesets is the ability to specify partition specific policies, limits,priorities, and scheduling algorithms although this feature is rarelyrequired. An example of this need may be a cluster consisting of 48nodes owned by the Astronomy Department and 16 nodes owned by theMathematics Department. Each department may be willing to allow sharingof resources but wants to specify how their partition will be used. Asmentioned earlier, many of the workload manager's scheduling policiesmay be specified on a per partition basis allowing each department tocontrol the scheduling goals within their partition.

The partition associated with each node should be specified as indicatedin the node location section. With this done, partition access lists maybe specified on a per job or per QOS basis to constrain which resourcesa job may have access to. By default, QOS's and jobs allow globalpartition access. Note that by default, a job may only utilize resourceswithin a single partition.

If no partition is specified, the workload manager creates one partitionper resource manager into which all resources corresponding to thatresource manager are placed. This partition may be given the same nameas the resource manager. A partition preferably does not span multipleresource managers. In addition to these resource manager partitions, apseudo-partition named [ALL] is created which contains the aggregateresources of all partitions. While the resource manager partitions arereal partitions containing resources not explicitly assigned to otherpartitions, the [ALL] partition is only a convenience object and is nota real partition; thus it cannot be requested by jobs or included inconfiguration ACL's.

Node-to-partition mappings are established using a node configurationparameter as shown in this example:

NODECFG[node001] PARTITION=astronomyNODECFG[node002] PARTITION=astronomy ... NODECFG[node049] PARTITION=math...

By default, the workload manager only allows the creation of 4partitions total. Two of these partitions, DEFAULT, and [ALL], are usedinternally, leaving only two additional partition definition slotsavailable. If more partitions will be needed, the maximum partitioncount should be adjusted. Increasing the maximum number of partitionscan be managed.

Determining who can use which partition is specified using *CFGparameters (for example, these parameters may be defined as: usercfg,groupcfg, accountcfg, quoscfg, classcfg and systemcfg). These parametersallow both a partition access list and default partition to be selectedon a credential or system wide basis using the PLIST and PDEF keywords.By default, the access associated with any given job is the logical orof all partition access lists assigned to the job's credentials. Assumea site with two partitions: general and test. The site management wouldlike everybody to use the general partition by default. However, oneuser, Steve, needs to perform the majority of his work on the testpartition. Two special groups, staff and mgmt will also need access touse the test partition from time to time but will perform most of theirwork in the general partition. The example configuration below willenable the needed user and group access and defaults for this site.

SYSCFG[base]  PLIST= USERCFG[DEFAULT] PLIST=generalUSERCFG[steve]  PLIST=general:test PDEF=testGROUPCFG[staff] PLIST=general:test PDEF=generalGROUPCFG[mgmt]  PLIST=general:test PDEF=general

By default, the system partition access list allows global access to allpartitions. If using logically or based partition access lists, thesystem partition list should be explicitly constrained using the SYSCFGparameter. While using a logical or approach allows sites to add accessto certain jobs, some sites prefer to work the other way around. Inthese cases, access is granted by default and certain credentials arethen restricted from access various partitions. To use this model, asystem partition list must be specified. See the example below:

SYSCFG[base] PLIST=general,test& USERCFG[demo] PLIST=test&GROUPCFG[staff] PLIST=general&

In the above example, note the ampersand (‘&’). This character, whichcan be located anywhere in the PLIST line, indicates that the specifiedpartition list should be logically AND'd with other partition accesslists. In this case, the configuration will limit jobs from user demo torunning in partition test and jobs from group staff to running inpartition general. All other jobs will be allowed to run in eitherpartition. When using and based partition access lists, the base systemaccess list must be specified with SYSCFG.

Users may request to use any partition they have access to on a per jobbasis. This is accomplished using the resource manager extensions, sincemost native batch systems do not support the partition concept. Forexample, on a PBS system, a job submitted by a member of the group staffcould request that the job run in the test partition by adding the line‘#PBS−W x=PARTITION:test’ to the command file. Special jobs may beallowed to span the resources of multiple partitions if desired byassociating the job with a QOS which has the flag ‘SPAN’ set.

The disclosure now continues to discuss reservations further. An advancereservation is the mechanism by which the present invention guaranteesthe availability of a set of resources at a particular time. With anadvanced reservation a site now has an ability to actually specify howthe scheduler should manage resources in both space and time. Everyreservation consists of three major components, a list of resources, atimeframe (a start and an end time during which it is active), and theACL. These elements are subject to a set of rules. The ACL acts as adoorway determining who or what can actually utilize the resources ofthe cluster. It is the job of the cluster scheduler to make certain thatthe ACL is not violated during the reservation's lifetime (i.e., itstimeframe) on the resources listed. The ACL governs access by thevarious users to the resources. The ACL does this by determining whichof the jobs, various groups, accounts, jobs with special service levels,jobs with requests for specific resource types or attributes and manydifferent aspects of requests can actually come in and utilize theresources. With the ability to say that these resources are reserved,the scheduler can then enforce true guarantees and can enforce policiesand enable dynamic administrative tasks to occur. The system greatlyincreases in efficiency because there is no need to partition theresources as was previously necessary and the administrative overhead isreduced it terms of staff time because things can be automated andscheduled ahead of time and reserved.

As an example of a reservation, a reservation may specify that node002is reserved for user John Doe on Friday. The scheduler will thus beconstrained to make certain that only John Doe's jobs can use node002 atany time on Friday. Advance reservation technology enables many featuresincluding backfill, deadline based scheduling, QOS support, and metascheduling.

There are several reservation concepts that will be introduced asaspects of the invention. These include dynamic reservations,co-allocating reservation resources of different types, reservationsthat self-optimize in time, reservations that self-optimization inspace, reservations rollbacks and reservation masks. The presentinvention relates to a system and method of providing dynamicreservations in a compute environment. Dynamic reservations arereservations that are able to be modified once they are created. Theworkload manager allows dynamic modification of most schedulingparameters allowing new scheduling policies, algorithms, constraints,and permissions to be set at any time. For example, a reservation may beexpanded or contracted after a job is submitted to more closely matchthe reservation to the workload. Changes made via client commands arepreferably temporary and will be overridden by values specified in aconfig files the next time the workload manager is shutdown andrestarted.

Various commands may be used manually or automatically to controlreservations. Examples of such commands and their function areillustrated in Table 3:

TABLE 3 mdiag -r display summarized reservation information and anymrsvctl unexpected state reservation control mrsvctl -r removereservations mrsvctl -c create an administrative reservation showresdisplay information regarding location and state of reservations

We now turn to the particular features of the present invention thatrelate to a system, method and computer readable medium for managingfuture policy enforcement within a compute environment. The method willbe typically practiced by a “system” or a computing device programmed tooperate and practice the steps of the method embodiment of theinvention. For example the system may have program modules configured tocarry out the particular instructions associated with the invention.

FIG. 6A illustrates a compute environment 600 having variousreservations therein 602, 604, 606, 608, 610. The compute environmentrepresents a node space map of jobs and reservations that exist withinthe environment. Generally, resources are represented on the y axis andtime on the x axis. Each of the reservations has a set of credentials,such as, for example, credentials associated with a user, a group,processors, nodes, quality of service, licensing rights and so forth. Asan example, a user may have a “credential” that requires that the usernever be able to reserve or consume more than 10 processors at a singletime. Feature 620 represents the limit on or policy associated with theparticular credential. Each row should be considered as having a maximumvalue for the respective credential. The method embodiment of theinvention is shown in FIG. 7 and will be discussed with reference toboth FIG. 6A, FIG. 6B and FIG. 7.

The method relates to managing future policy enforcement within acompute environment and comprises receiving a request for resources(702) which is shown in FIG. 6A as feature 614. The request 614 may befrom a user or a group and may relate to a job, a reservation associatedwith an existing job or some other object. Associated with the request614 are a series of credentials including, but not limited to, a limiton the total quantity of requests and limits on the number of resourcesthat may be available to any given credential at any given time. Thislimit is represented as feature 620. For example, a user may be limitedto having three jobs running at any given time on the compute resourcesor limited to a particular quality of service and so forth. The goal ofthe method is to allocated resources for the request at an optimizedtime within the computer environment 600 so that no policies areviolated. The optimization of the allocation may be in terms of time ormay be based on another parameter such as quality of service, efficientuse of resources as determined by an administrator, user, or otherentity, a credential of a user or a group and so forth.

The method comprises generating a mapping for each credential (704) thatindicates a total number of reserved resources and consumed resources atany given time frame considered. The mapping is preferably time-based.Reserved resources 622 are resources that are made available for a userto submit jobs. A mapping of consumed resources 628 indicates whatresources will be consumed by submitted jobs. In FIG. 6A, a mapping ofthe number of resources consumed by a user is shown by feature 630 withgraph 626. In each of these mappings, resources are on the y axis andtime is on the x axis. Graph 624 illustrates the reserved resources forthe user 630. Other credential maps are shown as well for group 632illustrating a mapping 634 for consumed resources and a mapping forreserved resources 636, processors 640 illustrating consumed resourcesmapping 642 and reserved resources mapping 644 and a quality of service(“Q”) 650 mapping illustrating consumed resource mapping 652 andreserved resource mapping 654.

For each credential map, the system generates a resource availabilitymap (706) such as that shown in FIG. 6A as feature 660. This mapidentifies the times and quantity of resources 662 that are availableindependent of any policies. In one aspect of the invention, the systemgenerates a resource availability map for each credential. The systemgenerates a first composite intersecting map for a first resource typeand a second composite intersecting map for a second resource type(708). For example, the first composite intersecting map for the firsttype of resource may relate to intersecting the resource availabilitymap 660 with each of the reserved resource mappings (622, 636, 644, 654)from the credential maps, thus generating an “IR” mapping or anintersecting reservation map. The second composite intersecting map forthe second type of resource may relate to intersecting the resourceavailability map and the mapping of consumed resources (628, 634, 642,652) for each credential map. It is noted that the composite maps alsomay comprise each credential mapping intersecting with each othercredential mapping and the resource availability mapping 660 to generatethe composite intersecting reservation mapping 672 or compositeintersecting consumed resources mapping 682.

The system then seeks to utilize these composite intersecting mappingsto allocate resources for the new request that optimizes a parameter.For example, the parameter may be time wherein the system seeks toallocate resources as soon as possible to accommodate the request or thejob. The system may identify a possible time for allocating resourcesbased on either the first composite map or the second composite map. Forexample, an allocation may be identified 674 that can start almostimmediately based on a composite mapping 670 of reserved resources 672.Similarly, the system may also identify a time and amount of resources684 based on an intersecting composite mapping 680 of consumed resources682.

In the case of using the consumed mapping first, the system may locatean earliest or best time that satisfies the consumed mapping. Theresources will then be any combination of reserved resources andunreserved resources that satisfy credential constraints. Therefore, thesystem has identified at the least a combination of resources that maybe allocated to handle the request. After checking against the consumedmapping to identify a group of resources that may be allocated at aparticular time, the system then may check for allocations against thereserved mapping at the same time. If the allocation favorably compareswith the reserve mapping, meaning that the allocation overlapscompletely with the non-consumed but reserved mapping, then the systemcan allocate resources at whatever time is best and can “go” anywherewithin the compute environment within the reserved space. If there arenot enough reserved resources, then the system must allocate newresources with constraints as will be explained further below.

The system will seek to optimize either the time or other parameter forallocating resources, that maintains all the policies and credentialsthat are in place, by utilizing the composite intersection mappings. Thesystem may do this in any number of ways and an example includes thefollowing. The system will identify or determine based on one of thefirst composite map or the second composite map (710). For example, asshown in FIG. 6B, the allocation 693 may be identified as an allocationthat may begin 2 hours from the present time and not overlap anypreviously reserved resources 692 and any consumed resources 694.Allocation 691 identifies resources that are previously reserved. Thesystem may, in one aspect of the invention, give preference to anallocation of previously reserved resources 691 because that user orgroup already “owns” those resources and no new resources would have tobe reserved or allocated to handle the request 614 or jobs submittedbased on the request. In this case, the allocation can be performedwithout any credential constraints because all of the identifiedresources were previously reserved and therefore automaticallyconforming to constraints for that user or group. Therefore, if theidentified resources do not overlap with consumed resources, and do notoverlap with available resources, the system may just proceed toallocate the resources 691 for the request 614 wherein the allocationalgorithm has complete freedom to allocate the resources at whatevertime is best or based on any other parameter.

However, even if allocation 691 can provide a resource allocationwithout constraints, the system may further determine whether anallocation may be made that is improved in some manner, such as timewherein the time at which a job may be submitted and consume may bemoved closer to the present time, which requires some further analysis.The allocation 697 is earlier in time and is shown as starting 1.5 hoursin the future. However, this new allocation is shown as partiallycovering previously reserved resources and would require a newallocation or a new reservation of resources. In this case, theallocation does not overlap consumed resources but new resources wouldhave to be reserved. As shown in FIG. 6B, the total resources for theallocation 696 includes a portion of previously reserved resources 695.Subtracting the previously reserved resources 695 from the total amount696 will provide the resources that need to be newly reserved. If thesystem determines to optimize the time of the allocation in this manner,the system then reserves or allocates the new resources according to theset of credentials such that no policies are violated.

FIG. 6C illustrates an example of identifying how many “n” number of newresources the system should reserve. For example, assume that allocation697 requires 8 processors and allocation 687 represents a portion of thepreviously reserved processors that are not to be consumed by submittedjobs. Feature 689 represents 9 consumed processors. The limit 620 is 22processors for the requestor. Resources 685 are shown as 10 non-reservedand processors available according to the credentials of the requestor.To identify how many un-reserved processors (or any other resource) toallocate, the system identifies that there are 22 total processors minusthe 12 total reserved. Of those 12, only three are identified as notbeing consumed and thus available for the request. The allocation 697would require 8 processors, therefore, the system determines that 5unreserved processors would have to be reserved for the request.Therefore, three processors may be allocated for the request withoutconstraints and 5 new processors must be newly reserved for the requestbut will be reserved with constraints. It is also preferred that anallocation algorithm in this case utilize as many of the previouslyreserved resources as possible in the allocation 697.

FIG. 6B also shows a space available at one hour for reservations in themapping. However, allocation 697 is shown as being 1.5 hours into thefuture to demonstrate that if a policy existed where the requestor couldnot reserve resources sooner than 1.5 hours into the future, then toenforce the policy for that user, the earliest time that the reservationfor request 614 may be made is at 1.5 hours as shown for allocation 697.

After performing the analysis above, and after optimizing a parametersuch as time for identifying a time and an amount of resources that maybe used to satisfy the request 614, the system will allocate resourceswithin the compute environment based on at least one of the first or thesecond composite mappings (712). Other composite mappings may also beutilized to further optimize the time and allocation of resources. Forexample, more than two composite maps may be generated as part of theanalysis to identify resources, comply with credentials and policies,and optimize reservations.

Another aspect of the invention shown in FIGS. 6 and 7 relates toidentifying the earliest time that all policies may be satisfied afterthe intersection of each policy credential with the resourceavailability map 638 and assuming based on statistics a placement of anew resource availability. This can achieve a high percentage of successand where the assumption is incorrect, in other words where anassumption that a resource is available for a job turns out to beincorrect because the resource is reserved or will be consumed by asubmitted job, the system can dynamically adjust the new reservation toavoid the newly identified conflict.

One advantage of the invention is that it enables the system to analyzeresources for the request based on a mapping of reserved resources andthen identify a possible allocation. For example, a time frame forstarting a job on the resources in two hours that provides noconstraints for the allocation algorithm. This is illustrated by feature693. Then the system can generate a composite mapping of the consumedresources and possibly identify a sooner time or other improvedparameter for the allocation, even if it is under a set of constraintsfully or partially. For example, moving the allocation forward in timemay require reserving new resources not previously reserved for therequestor. Those resources will be reserved according to the knownconstraints. If a portion of the resources for the allocation werepreviously reserved for the requestor, then no constraints are neededfor that portion of the allocation.

Embodiments within the scope of the present invention may also includecomputer-readable media for carrying or having computer-executableinstructions or data structures stored thereon. Such computer-readablemedia can be any available media that can be accessed by a generalpurpose or special purpose computer. By way of example, and notlimitation, such computer-readable media can comprise RAM, ROM, EEPROM,CD-ROM or other optical disk storage, magnetic disk storage or othermagnetic storage devices, or any other medium which can be used to carryor store desired program code means in the form of computer-executableinstructions or data structures. When information is transferred orprovided over a network or another communications connection (eitherhardwired, wireless, or combination thereof) to a computer, the computerproperly views the connection as a computer-readable medium. Thus, anysuch connection is properly termed a computer-readable medium.Combinations of the above should also be included within the scope ofthe computer-readable media.

Computer-executable instructions include, for example, instructions anddata which cause a general purpose computer, special purpose computer,or special purpose processing device to perform a certain function orgroup of functions. Computer-executable instructions also includeprogram modules that are executed by computers in stand-alone or networkenvironments. Generally, program modules include routines, programs,objects, components, and data structures, etc. that perform particulartasks or implement particular abstract data types. Computer-executableinstructions, associated data structures, and program modules representexamples of the program code means for executing steps of the methodsdisclosed herein. The particular sequence of such executableinstructions or associated data structures represents examples ofcorresponding acts for implementing the functions described in suchsteps.

Those of skill in the art will appreciate that other embodiments of theinvention may be practiced in network computing environments with manytypes of computer system configurations, including personal computers,hand-held devices, multi-processor systems, microprocessor-based orprogrammable consumer electronics, network PCs, minicomputers, mainframecomputers, and the like. Embodiments may also be practiced indistributed computing environments where tasks are performed by localand remote processing devices that are linked (either by hardwiredlinks, wireless links, or by a combination thereof) through acommunications network. In a distributed computing environment, programmodules may be located in both local and remote memory storage devices.

Although the above description may contain specific details, they shouldnot be construed as limiting the claims in any way. Other configurationsof the described embodiments of the invention are part of the scope ofthis invention. Accordingly, the appended claims and their legalequivalents should only define the invention, rather than any specificexamples given.

I claim:
 1. A method comprising: establishing a standing reservation viaa workload manager for compute resources within a compute environment,wherein the standing reservation is periodic and comprises a firstreservation of a group of compute resources at a first time to yield afirst group of reserved compute resources and a second reservation ofthe group of compute resources at a second time to yield a second groupof reserved compute resources; receiving a request for compute resourcesto process workload in the standing reservation; receiving, with therequest, an optimization request for the workload, wherein theoptimization request causes the workload manager to analyze the computeenvironment for opportunities to modify, prior to the computeenvironment processing the workload, one of the first group of reservedcompute resources and the second group of reserved compute resources interms of one of space or time to improve performance of the computeenvironment when the compute environment processes the workload relativeto a configuration of the compute environment under the standingreservation at a time the request for compute resources was received;modifying, via virtual partitioning, one of the first group of reservedcompute resources and the second group of reserved compute resourcesaccording to the optimization request to yield a modified group ofcompute resources; and inserting the workload into the modified group ofcompute resources for processing.
 2. The method of claim 1, wherein theworkload manager receives requests for the compute resources in thecompute environment and makes reservations for the compute resources toaccommodate the requests.
 3. The method of claim 1, wherein the standingreservation is created and configured by specifying parameters in aconfiguration file.
 4. The method of claim 1, wherein the optimizationrequest for the workload has one of a required criteria, a preferredcriteria, and both the required criteria and the preferred criteria. 5.The method of claim 1, wherein the virtual partitioning comprises makingmodifications based on one of criteria, class, quality of service, andpolicies.
 6. The method of claim 5, wherein the virtual partitioningcomprises modifying one of the first group of reserved computeresources, the second group of reserved compute resources, and both thefirst group of reserved compute resources and the second group ofreserved compute resources.
 7. The method of claim 1, wherein the useris a group of users.
 8. A system comprising a processor; and acomputer-readable medium storing instructions, which, when executed bythe processor, cause the processor to perform operations comprising:establishing a standing reservation via a workload manager for computeresources within a compute environment, wherein the standing reservationis periodic and comprises a first reservation of a group of computeresources at a first time to yield a first group of reserved computeresources and a second reservation of the group of compute resources ata second time to yield a second group of reserved compute resources;receiving a request for compute resources to process workload in thestanding reservation; receiving, with the request, an optimizationrequest for the workload, wherein the optimization request causes theworkload manager to analyze the compute environment for opportunities tomodify, prior to the compute environment processing the workload, one ofthe first group of reserved compute resources and the second group ofreserved compute resources in terms of one of space or time to improveperformance of the compute environment when the compute environmentprocesses the workload relative to a configuration of the computeenvironment under the standing reservation at a time the request forcompute resources was received; modifying, via virtual partitioning, oneof the first group of reserved compute resources and the second group ofreserved compute resources according to the optimization request toyield a modified group of compute resources; and inserting the workloadinto the modified group of compute resources for processing.
 9. Thesystem of claim 8, wherein the workload manager receives requests forthe compute resources in the compute environment and makes reservationsfor the compute resources to accommodate the requests.
 10. The system ofclaim 8, wherein the standing reservation is created and configured byspecifying parameters in a configuration file.
 11. The system of claim8, wherein the optimization request for the workload has one of arequired criteria, a preferred criteria, and both the required criteriaand the preferred criteria.
 12. The system of claim 8, wherein thevirtual partitioning comprises making modifications based on one ofcriteria, class, quality of service, and policies.
 13. The system ofclaim 12, wherein the virtual partitioning comprises modifying one ofthe first group of reserved compute resources, the second group ofreserved compute resources, and both the first group of reserved computeresources and the second group of reserved compute resources.
 14. Thesystem of claim 8, wherein the user is a group of users.
 15. Acomputer-readable storage device storing instructions for controlling acomputing device to process a request for resources within a computeenvironment, the instructions, when extracted by the computing device,cause the computing device to perform operations comprising:establishing a standing reservation via a workload manager for computeresources within a compute environment, wherein the standing reservationis periodic and comprises a first reservation of a group of computeresources at a first time to yield a first group of reserved computeresources and a second reservation of the group of compute resources ata second time to yield a second group of reserved compute resources;receiving a request for compute resources to process workload in thestanding reservation; receiving, with the request, an optimizationrequest for the workload wherein the optimization request causes theworkload manager to analyze the compute environment for opportunities tomodify, prior to the compute environment processing the workload, one ofthe first group of reserved compute resources and the second group ofreserved compute resources in terms of one of space or time to improveperformance of the compute environment when the compute environmentprocesses the workload relative to a configuration of the computeenvironment under the standing reservation at a time the request forcompute resources was received; modifying, via virtual partitioning, oneof the first group of reserved compute resources and the second group ofreserved compute resources according to the optimization request toyield a modified group of compute resources; and inserting the workloadinto the modified group of compute resources for processing.
 16. Thecomputer-readable storage device of claim 15, wherein the standingreservation is created and configured by specifying parameters in aconfiguration file.
 17. The computer-readable storage device of claim15, wherein the optimization request for the workload has one of arequired criteria, a preferred criteria, and both the required criteriaand the preferred criteria.
 18. The computer-readable storage device ofclaim 15, wherein the virtual partitioning comprises makingmodifications based on one of criteria, class, quality of service, andpolicies.
 19. The computer-readable storage device of claim 18, whereinthe virtual partitioning comprises modifying one of the first group ofreserved compute resources, the second group of reserved computeresources, and both the first group of reserved compute resources andthe second group of reserved compute resources.
 20. Thecomputer-readable storage device of claim 15, wherein the user is agroup of users.